U.S. patent application number 17/453031 was filed with the patent office on 2022-05-05 for method and system for inspecting and detecting fluid in a pipeline.
This patent application is currently assigned to Tata Consultancy Services Limited. The applicant listed for this patent is Tata Consultancy Services Limited. Invention is credited to Chirabrata Bhaumik, Tapas Chakravarty, Abhijeet Gorey, Gitesh Kulkarni, Arpan Pal, Arijit Sinharay.
Application Number | 20220136924 17/453031 |
Document ID | / |
Family ID | |
Filed Date | 2022-05-05 |
United States Patent
Application |
20220136924 |
Kind Code |
A1 |
Sinharay; Arijit ; et
al. |
May 5, 2022 |
METHOD AND SYSTEM FOR INSPECTING AND DETECTING FLUID IN A
PIPELINE
Abstract
Fluids are normally transported from one place to another
through pipelines. It is essential to monitor the pipeline to avoid
leakage or theft. It is expensive and not feasible to install
cameras and sensors along the whole length of the pipeline. A
system and method for inspecting and detecting fluid leakage in a
pipeline has been provided. The system is using vibration sensors
along with pressure sensors to detect the leakage or theft along
with the exact location of the leakage or theft. The pressure
sensors are mounted on the pipeline so that the fluid touches the
diaphragm of the pressure sensors to sense the wave generated due
to leakage. The vibration sensors are mounted on top of the
pipeline surface and on the nearby ground to eliminate general
noise conditions. Moreover, two pressure sensors are also installed
at opposite sides to pinpoint the leakage location.
Inventors: |
Sinharay; Arijit; (Kolkata,
IN) ; Kulkarni; Gitesh; (Bangalore, IN) ;
Gorey; Abhijeet; (Kolkata, IN) ; Bhaumik;
Chirabrata; (Kolkata, IN) ; Chakravarty; Tapas;
(Kolkata, IN) ; Pal; Arpan; (Kolkata, IN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Tata Consultancy Services Limited |
Mumbai |
|
IN |
|
|
Assignee: |
Tata Consultancy Services
Limited
Mumbai
IN
|
Appl. No.: |
17/453031 |
Filed: |
November 1, 2021 |
International
Class: |
G01M 3/24 20060101
G01M003/24; G01S 19/01 20060101 G01S019/01 |
Foreign Application Data
Date |
Code |
Application Number |
Nov 2, 2020 |
IN |
202021047845 |
Claims
1. A processor implemented method for inspecting and detecting
fluid leakage in a pipeline, the method comprising: capturing
vibration signals from a first vibration sensor, a second vibration
sensor, a third vibration sensor and a fourth vibration sensor,
wherein the first vibration sensor is installed at a first location
on the pipeline, the second vibration sensor is installed at a
second location on the pipeline, wherein the first location and the
second location are two ends of a segment from amongst a plurality
of segments of the pipeline, wherein the plurality of segments is
distributed along a length of the pipeline at equal distance from
each other, the third vibration sensor is installed at the first
location on ground, and the fourth vibration sensor is installed at
the second location on the ground; capturing negative pressure wave
signals generated due to leakage in the pipeline using a first
pressure sensor and a second pressure sensor, wherein the first
pressure sensor is installed at the first location on the pipeline,
and the second pressure sensor is installed at the second location
on the pipeline; calculating, via one or more hardware processors,
a first signal (S1) as a difference between signals captured from
the first vibration sensor and the third vibration sensor present
at the first location; calculating, via the one or more hardware
processors, a second signal (S2) as a difference between signals
captured from the second vibration sensor and the fourth vibration
sensor present at the second location; calculating, via the one or
more hardware processors, a third signal (S3) as a difference
between signals captured from the first pressure sensor and the
third vibration sensor; calculating, via the one or more hardware
processors, a fourth signal (S4) as a difference between signals
captured from the second pressure sensor and the fourth vibration
sensor; digitizing, via the one or more hardware processors, the
first signal (S1), the second signal (S2), the third signal (S3),
and the fourth signal (S4) along with a global positioning system
(GPS) time stamping; extracting, via the one or more hardware
processors, a plurality of features from a one-minute time window
of each of the first signal (S1), the second signal (S2), the third
signal (S3), and the fourth signal (S4); selecting, via the one or
more hardware processors, a set of features out of the plurality of
features using a feature selection algorithm, wherein the set of
features are selected based on user defined condition; providing,
via the one or more hardware processors, the selected set of
features to a pre-generated classifier model, wherein the
pre-generated classifier model is generated by simulating a normal
condition, a leakage condition and a theft condition; and
detecting, via the one or more hardware processors, at least one of
the normal condition, the leakage condition in the pipeline and the
theft condition in the pipeline using the pre-generated classifier
model.
2. The method of claim 1 further comprising identifying an exact
location of the leakage or the theft along the length of the
pipeline.
3. The method of claim 2, wherein identifying the exact location of
the leakage is determined using following equation: X L = L - v
.times. .times. .DELTA. .times. .times. tl 2 , ##EQU00003## where,
X.sub.L is the exact location of the leakage, L is the length of
the segment, .DELTA.tl is the time delay between the third signal
S3 and the fourth signal S4, and v is the sound speed in pipe
metal.
4. The method of claim 2, wherein identifying the exact location of
the theft is determined using following equation: X T = L - v
.times. .times. .DELTA. .times. .times. tt 2 , ##EQU00004## where,
X.sub.T is the exact location of the theft, L is the length of the
segment, .DELTA.tt is the time delay between the first signal S1
and the second signal S2, and v is the sound speed in pipe
metal.
5. The method of claim 1 further comprising generating an alarm in
case of detection of the leakage or the theft.
6. The method of claim 1, wherein the step of providing the
selected set of features to a pre-generated classifier model is
preceded by the following steps: simulating the leakage condition
in the pipeline for a predefined time window; capturing the first
signal (S1), the second signal (S2), the third signal (S3), and the
fourth signal (S4) corresponding to the leakage condition;
digitizing, via the one or more hardware processors, the first
signal (S1), the second signal (S2), the third signal (S3), and the
fourth signal (S4) corresponding to the leakage condition with a
global positioning system (GPS) time stamping; labelling the
digitized signal corresponding to the leakage condition as class 1;
simulating the theft condition in the pipeline for the predefined
time window; capturing the first signal (S1), the second signal
(S2), the third signal (S3), and the fourth signal (S4)
corresponding to the theft condition; digitizing, via the one or
more hardware processors, the first signal (S1), the second signal
(S2), the third signal (S3), and the fourth signal (S4)
corresponding to the theft condition with the global positioning
system (GPS) time stamping; labelling the digitized signal
corresponding to the theft condition as class 2; simulating the
normal condition in the pipeline for the predefined time window;
capturing the first signal (S1), the second signal (S2), the third
signal (S3), and the fourth signal (S4) corresponding to the normal
condition; digitizing, via the one or more hardware processors, the
first signal (S1), the second signal (S2), the third signal (S3),
and the fourth signal (S4) corresponding to the normal condition
with the global positioning system (GPS) time stamping; labelling
the digitized signal corresponding to the normal condition as class
3; extracting the plurality of features from the predefined time
window of each of the first signal (S1), the second signal (S2),
the third signal (S3), and the fourth signal (S4); selecting, via
the one or more hardware processors, the set of features out of the
plurality of features using the feature selection algorithm,
wherein the set of features are best features selected based on the
predefined condition; and obtaining the pre-generated classifier
model using the selected set of features.
7. The method of claim 1, wherein the step of detecting, at least
one of the normal condition, the leakage in the pipeline or the
theft in the pipeline comprises identifying the normal condition,
the leakage condition and the theft condition if the classifier
model predicts the class 3, class 1 and the class 2
respectively.
8. The method of claim 1, wherein the plurality of features
comprises a plurality of time-frequency based features and a
plurality of statistical features.
9. A system for inspecting and detecting fluid leakage in a
pipeline, the system comprises: a first vibration sensor (A), a
second vibration sensor (B), a third vibration sensor (C) and a
fourth vibration sensor (D) for capturing vibration signals,
wherein the first vibration sensor (A) is installed at a first
location on the pipeline, the second vibration sensor is installed
at a second location on the pipeline, wherein the first location
and the second location are two ends of a segment from amongst a
plurality of segments of the pipeline, wherein the plurality of
segments is distributed along a length of the pipeline at equal
distance from each other, the third vibration sensor is installed
at the first location on ground, and the fourth vibration sensor is
installed at the second location on the ground; a first pressure
sensor (P1) and a second pressure sensor (P2) for capturing
negative pressure wave signals generated due to leakage in the
pipeline, wherein the first pressure sensor is installed at the
first location on the pipeline, and the second pressure sensor is
installed at the second location on the pipeline; one or more
hardware processors; a memory in communication with the one or more
hardware processors, wherein the one or more first hardware
processors are configured to execute programmed instructions stored
in the one or more first memories, to: calculate, a first signal
(S1) as a difference between the signals captured from the first
vibration sensor and the third vibration sensor present at the
first location; calculate a second signal (S2) as a difference
between the signals captured from the second vibration sensor and
the fourth vibration sensor present at the second location;
calculate a third signal (S3) as a difference between the signals
captured from the first pressure sensor and the third vibration
sensor; calculate a fourth signal (S4) as a difference between the
signals captured from the second pressure sensor and the fourth
vibration sensor; digitize the first signal (S1), the second signal
(S2), the third signal (S3), and the fourth signal (S4) along with
a global positioning system (GPS) time stamping; extract a
plurality of features from a one-minute time window of each of the
first signal (S1), the second signal (S2), the third signal (S3),
and the fourth signal (S4); select a set of features out of the
plurality of features using a feature selection algorithm, wherein
the set of features are selected based on user defined condition;
provide the selected set of features to a pre-generated classifier
model, wherein the pre-generated classifier model is generated by
simulating a normal condition, a leakage condition and a theft
condition; and detect at least one of the normal condition, the
leakage condition in the pipeline and the theft condition in the
pipeline using the pre-generated classifier model.
10. The system of claim 9 further configured to identify an exact
location of the leakage or the theft along the length of the
pipeline.
11. The system of claim 10, wherein identifying the exact location
of the leakage is determined using following equation: X L = L - v
.times. .times. .DELTA. .times. .times. tl 2 , ##EQU00005## where,
X.sub.L is the exact location of the leakage, L is the length of
the segment, .DELTA.tl is the time delay between the third signal
S3 and the fourth signal S4, and v is the sound speed in pipe
metal.
12. The system of claim 10, wherein identifying the exact location
of the theft is determined using following equation: X T = L - v
.times. .times. .DELTA. .times. .times. tt 2 , ##EQU00006## where,
X.sub.T is the exact location of the theft, L is the length of the
segment, .DELTA.tt is the time delay between the first signal S1
and the second signal S2, and v is the sound speed in pipe
metal.
13. The system of claim 9 further configured to generate an alarm
in case of detection of the leakage or the theft.
14. One or more non-transitory machine readable information storage
mediums comprising one or more instructions which when executed by
one or more hardware processors cause managing a plurality of
events, the instructions cause: capturing vibration signals from a
first vibration sensor, a second vibration sensor, a third
vibration sensor and a fourth vibration sensor, wherein the first
vibration sensor is installed at a first location on the pipeline,
the second vibration sensor is installed at a second location on
the pipeline, wherein the first location and the second location
are two ends of a segment from amongst a plurality of segments of
the pipeline, wherein the plurality of segments is distributed
along a length of the pipeline at equal distance from each other,
the third vibration sensor is installed at the first location on
ground, and the fourth vibration sensor is installed at the second
location on the ground; capturing negative pressure wave signals
generated due to leakage in the pipeline using a first pressure
sensor and a second pressure sensor, wherein the first pressure
sensor is installed at the first location on the pipeline, and the
second pressure sensor is installed at the second location on the
pipeline; calculating a first signal (S1) as a difference between
signals captured from the first vibration sensor and the third
vibration sensor present at the first location; calculating a
second signal (S2) as a difference between signals captured from
the second vibration sensor and the fourth vibration sensor present
at the second location; calculating a third signal (S3) as a
difference between signals captured from the first pressure sensor
and the third vibration sensor; calculating a fourth signal (S4) as
a difference between signals captured from the second pressure
sensor and the fourth vibration sensor; digitizing the first signal
(S1), the second signal (S2), the third signal (S3), and the fourth
signal (S4) along with a global positioning system (GPS) time
stamping; extracting a plurality of features from a one-minute time
window of each of the first signal (S1), the second signal (S2),
the third signal (S3), and the fourth signal (S4); selecting a set
of features out of the plurality of features using a feature
selection algorithm, wherein the set of features are selected based
on user defined condition; providing the selected set of features
to a pre-generated classifier model, wherein the pre-generated
classifier model is generated by simulating a normal condition, a
leakage condition and a theft condition; and detecting at least one
of the normal condition, the leakage condition in the pipeline and
the theft condition in the pipeline using the pre-generated
classifier model.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS AND PRIORITY
[0001] This U.S. patent application claims priority under 35 U.S.C.
.sctn. 119 to: India Application No. 202021047845, filed on Nov. 2,
2020. The entire contents of the aforementioned application are
incorporated herein by reference.
TECHNICAL FIELD
[0002] The disclosure herein generally relates to the field of
fluid leak detection, and, more particularly, to a method and
system for inspecting and detecting fluid such as oil and gas
leakage in a pipeline.
BACKGROUND
[0003] Various fluids such as oils and gases are normally
transported from one place to another through pipelines which run
up to thousands of kilometers. Due to various reasons, there are
chances of leakage of fluid from the pipeline.
[0004] Timely leak detection in oil and gas pipelines is essential
to protect economic loss as well as possible catastrophe. In
addition to that there are also probability of theft of oils and
gases. Therefore, it is essential to monitor the pipeline to avoid
such kind of instances.
[0005] One of the traditional methods used in the prior art is to
install sensors or cameras at a regular distance to monitor the
pipelines. Since oil and gas pipelines runs more than thousand
kilometers, it is not feasible to put frequent sensors on the
pipeline as it makes the installation cost as well as maintenance
too high to afford and difficult to operate. So sensing technique
is required to probe long segment of pipelines in an affordable
manner.
SUMMARY
[0006] Embodiments of the present disclosure present technological
improvements as solutions to one or more of the above-mentioned
technical problems recognized by the inventors in conventional
systems. For example, in one embodiment, a system for inspecting
and detecting fluid leakage in a pipeline is provided. The system
comprises a first vibration sensor, a second vibration sensor, a
third vibration sensor, a fourth vibration sensor, a first pressure
sensor, a second pressure sensor, one or more hardware processors
and a memory. The first vibration sensor, the second vibration
sensor, the third vibration sensor, and the fourth vibration sensor
capture vibration signals. The first vibration sensor is installed
at a first location on the pipeline. The second vibration sensor is
installed at a second location on the pipeline, wherein the first
location and the second location are two ends of a segment from
amongst a plurality of segments of the pipeline, wherein the
plurality of segments is distributed along a length of the pipeline
at equal distance from each other. The third vibration sensor is
installed at the first location on ground. The fourth vibration
sensor is installed at the second location on the ground. The first
pressure sensor and the second pressure sensor capture negative
pressure wave signals generated due to leakage in the pipeline. The
first pressure sensor is installed at the first location on the
pipeline. The second pressure sensor is installed at the second
location on the pipeline. The memory is in communication with the
one or more hardware processors, wherein the one or more first
hardware processors are configured to execute programmed
instructions stored in the one or more first memories, to:
calculate, a first signal (S1) as a difference between the signals
captured from the first vibration sensor and the third vibration
sensor present at the first location; calculate a second signal
(S2) as a difference between the signals captured from the second
vibration sensor and the fourth vibration sensor present at the
second location; calculate a third signal (S3) as a difference
between the signals captured from the first pressure sensor and the
third vibration sensor; calculate a fourth signal (S4) as a
difference between the signals captured from the second pressure
sensor and the fourth vibration sensor; digitize the first signal
(S1), the second signal (S2), the third signal (S3), and the fourth
signal (S4) along with a global positioning system (GPS) time
stamping; extract a plurality of features from a one-minute time
window of each of the first signal (S1), the second signal (S2),
the third signal (S3), and the fourth signal (S4); select a set of
features out of the plurality of features using a feature selection
algorithm, wherein the set of features are selected based on user
defined condition; provide the selected set of features to a
pre-generated classifier model, wherein the pre-generated
classifier model is generated by simulating a normal condition, a
leakage condition and a theft condition; and detect at least one of
the normal condition, the leakage condition in the pipeline and the
theft condition in the pipeline using the pre-generated classifier
model.
[0007] In another aspect, a method for inspecting and detecting
fluid leakage in a pipeline is provided. Initially, vibration
signals are captured from a first vibration sensor, a second
vibration sensor, a third vibration sensor and a fourth vibration
sensor. The first vibration sensor is installed at a first location
on the pipeline. The second vibration sensor is installed at a
second location on the pipeline, wherein the first location and the
second location are two ends of a segment from amongst a plurality
of segments of the pipeline, wherein the plurality of segments is
distributed along a length of the pipeline at equal distance from
each other. The third vibration sensor is installed at the first
location on ground. The fourth vibration sensor is installed at the
second location on the ground. In the next step, negative pressure
wave signals generated due to leakage in the pipeline are captured
using a first pressure sensor and a second pressure sensor. The
first pressure sensor is installed at the first location on the
pipeline, and the second pressure sensor is installed at the second
location on the pipeline. Further, a first signal (S1) is
calculated as a difference between signals captured from the first
vibration sensor and the third vibration sensor present at the
first location. A second signal (S2) is calculated as a difference
between signals captured from the second vibration sensor and the
fourth vibration sensor present at the second location. A third
signal (S3) is calculated as a difference between signals captured
from the first pressure sensor and the third vibration sensor. A
fourth signal (S4) is calculated as a difference between signals
captured from the second pressure sensor and the fourth vibration
sensor. In the next step, the first signal (S1), the second signal
(S2), the third signal (S3), and the fourth signal (S4) are
digitized along with a global positioning system (GPS) time
stamping. A plurality of features is then extracted from a
one-minute time window of each of the first signal (S1), the second
signal (S2), the third signal (S3), and the fourth signal (S4).
Further, a set of features is selected out of the plurality of
features using a feature selection algorithm, wherein the set of
features are selected based on user defined condition. In the next
step, the selected set of features is provided to a pre-generated
classifier model, wherein the pre-generated classifier model is
generated by simulating a normal condition, a leakage condition and
a theft condition. And finally, at least one of the normal
condition, the leakage condition in the pipeline and the theft
condition in the pipeline is detected using the pre-generated
classifier model.
[0008] In yet another aspect, one or more non-transitory
machine-readable information storage mediums comprising one or more
instructions which when executed by one or more hardware processors
cause inspecting and detecting fluid leakage in a pipeline is
provided. Initially, vibration signals are captured from a first
vibration sensor, a second vibration sensor, a third vibration
sensor and a fourth vibration sensor. The first vibration sensor is
installed at a first location on the pipeline. The second vibration
sensor is installed at a second location on the pipeline, wherein
the first location and the second location are two ends of a
segment from amongst a plurality of segments of the pipeline,
wherein the plurality of segments is distributed along a length of
the pipeline at equal distance from each other. The third vibration
sensor is installed at the first location on ground. The fourth
vibration sensor is installed at the second location on the ground.
In the next step, negative pressure wave signals generated due to
leakage in the pipeline are captured using a first pressure sensor
and a second pressure sensor. The first pressure sensor is
installed at the first location on the pipeline, and the second
pressure sensor is installed at the second location on the
pipeline. Further, a first signal (S1) is calculated as a
difference between signals captured from the first vibration sensor
and the third vibration sensor present at the first location. A
second signal (S2) is calculated as a difference between signals
captured from the second vibration sensor and the fourth vibration
sensor present at the second location. A third signal (S3) is
calculated as a difference between signals captured from the first
pressure sensor and the third vibration sensor. A fourth signal
(S4) is calculated as a difference between signals captured from
the second pressure sensor and the fourth vibration sensor. In the
next step, the first signal (S1), the second signal (S2), the third
signal (S3), and the fourth signal (S4) are digitized along with a
global positioning system (GPS) time stamping. A plurality of
features is then extracted from a one-minute time window of each of
the first signal (S1), the second signal (S2), the third signal
(S3), and the fourth signal (S4). Further, a set of features is
selected out of the plurality of features using a feature selection
algorithm, wherein the set of features are selected based on user
defined condition. In the next step, the selected set of features
is provided to a pre-generated classifier model, wherein the
pre-generated classifier model is generated by simulating a normal
condition, a leakage condition and a theft condition. And finally,
at least one of the normal condition, the leakage condition in the
pipeline and the theft condition in the pipeline is detected using
the pre-generated classifier model.
[0009] It is to be understood that both the foregoing general
description and the following detailed description are exemplary
and explanatory only and are not restrictive of the invention, as
claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The accompanying drawings, which are incorporated in and
constitute a part of this disclosure, illustrate exemplary
embodiments and, together with the description, serve to explain
the disclosed principles:
[0011] FIG. 1 illustrates a block diagram of a system for
inspecting and detecting fluid leakage in a pipeline according to
some embodiments of the present disclosure.
[0012] FIG. 2 is a schematic diagram of the system (of FIG. 1) for
inspecting and detecting fluid leakage in a pipeline according to
some embodiments of the present disclosure.
[0013] FIG. 3 illustrates a flowchart for generating a classifier
model in accordance with some embodiments of the present
disclosure.
[0014] FIG. 4A through FIG. 4B is a flow diagram illustrating
inspecting and detecting fluid leakage in the pipeline in
accordance with some embodiments of the present disclosure.
[0015] FIG. 5 is a flowchart showing steps involved in
classification using the classifier model in accordance with some
embodiments of the present disclosure.
DETAILED DESCRIPTION OF EMBODIMENTS
[0016] Exemplary embodiments are described with reference to the
accompanying drawings. In the figures, the left-most digit(s) of a
reference number identifies the figure in which the reference
number first appears. Wherever convenient, the same reference
numbers are used throughout the drawings to refer to the same or
like parts. While examples and features of disclosed principles are
described herein, modifications, adaptations, and other
implementations are possible without departing from the scope of
the disclosed embodiments.
[0017] Oils, gases, chemicals and other fluids are normally
transported from one place to another through the pipelines. Due to
various reasons, there are chance of leakage of fluid from the
pipeline. It is essential to monitor the pipeline to avoid such
kind of instances. There exist few methods in the art for timely
detection of leakage and theft of oils and gases. There is also an
optic based technique used for the sensing. In this technique, four
layers of optic fibers need to be laid along the pipeline to work
smoothly and optimally. So, installation is very challenging, and
it increases the cost of installation and maintenance.
[0018] The present disclosure herein provides a system and a method
for inspecting and detecting fluids such as oil and gas leakage in
a pipeline. The system is using a plurality of vibration sensors
along with a plurality of pressure sensors to detect the leakage or
theft along with the exact location of the leakage or theft. The
plurality of pressure sensors is mounted on the pipeline so that
the fluid touches the diaphragm of the plurality of pressure
sensors. The plurality of vibration sensors is mounted on top of
the pipeline surface. Further, another vibration sensor is also
mounted on the nearby ground to eliminate general noise conditions
(seismic waves, etc.). Since the negative pressure waves contain
low frequency waves (infrasound range) it can travel a long
distance through the fluid inside the pipeline. Thus, the pressure
sensors can register arrival of such waves to indicate possible
leakage. Moreover, two such sensors installed at opposite sides can
pin point the leakage location. However, very small leakages or oil
drains building up slowly (theft operation) may not trigger the
negative pressure waves and cannot be detected by the installed
pressure sensor. Here, the plurality of vibration sensors installed
on the pipe surface are configured to sense distinct infrasonic
vibrations signatures generated by the small leakages.
[0019] The transportation of fluid across the pipelines are
generally under pressure, i.e., the pipelines have a high pressure
inside them. Whenever there is a disturbance in the pipeline due to
leakage or some other reason, there is a change in the pressure
inside the pipeline, which is called as a negative pressure. The
negative pressure travels in both directions, upstream and
downstream. The negative pressure waves are generally in a low
frequency range in the range of 50 Hz to 100 Hz, it can travel to a
long distance up to 10 miles. These negative pressure waves can be
sensed using the pressure sensors. In addition to that, the
negative pressure also contains some infrasound range of pressure
waves, which can be also sensed. Further, not only sensing, it is
also possible to pin point the exact location of the leakage or
disturbance along the pipeline.
[0020] Referring now to the drawings, and more particularly to FIG.
1 through FIG. 5, where similar reference characters denote
corresponding features consistently throughout the figures, there
are shown preferred embodiments and these embodiments are described
in the context of the following exemplary system and/or method.
[0021] FIG. 1 illustrates a block diagram of a system 100 and FIG.
2 is a schematic diagram of the system 100 for inspecting and
detecting fluid leakage in a pipeline 102. Although the present
disclosure is explained considering that the system 100 is
implemented on a server, it may also be present elsewhere such as a
local machine. It may be understood that the system 100 comprises
one or more computing devices 104, such as a laptop computer, a
desktop computer, a notebook, a workstation, a cloud-based
computing environment and the like. It will be understood that the
system 100 may be accessed through one or more input/output
interfaces collectively referred to as I/O interface 106. Examples
of the I/O interface 106 may include, but are not limited to, a
user interface, a portable computer, a personal digital assistant,
a handheld device, a smartphone, a tablet computer, a workstation
and the like. The I/O interface 106 are communicatively coupled to
the system 100 through a network 108.
[0022] In an embodiment, the network 108 may be a wireless or a
wired network, or a combination thereof. In an example, the network
108 can be implemented as a computer network, as one of the
different types of networks, such as virtual private network (VPN),
intranet, local area network (LAN), wide area network (WAN), the
internet, and such. The network 108 may either be a dedicated
network or a shared network, which represents an association of the
different types of networks that use a variety of protocols, for
example, Hypertext Transfer Protocol (HTTP), Transmission Control
Protocol/Internet Protocol (TCP/IP), and Wireless Application
Protocol (WAP), to communicate with each other. Further, the
network 108 may include a variety of network devices, including
routers, bridges, servers, computing devices, storage devices. The
network devices within the network 108 may interact with the system
100 through communication links.
[0023] The system 100 may be implemented in a workstation, a
mainframe computer, a server, and a network server. In an
embodiment, the computing device 104 further comprises one or more
hardware processors 110, one or more memory 112, hereinafter
referred as a memory 112 and a data repository 114, for example, a
repository 114 or a database 114. The memory 112 is in
communication with the one or more hardware processors 110, wherein
the one or more hardware processors 110 are configured to execute
programmed instructions stored in the memory 112, to perform
various functions as explained in the later part of the disclosure.
The repository 114 may store data processed, received, and
generated by the system 100.
[0024] The system 100 supports various connectivity options such as
BLUETOOTH.RTM., USB, ZigBee and other cellular services. The
network environment enables connection of various components of the
system 100 using any communication link including Internet, WAN,
MAN, and so on. In an exemplary embodiment, the system 100 is
implemented to operate as a stand-alone device. In another
embodiment, the system 100 may be implemented to work as a loosely
coupled device to a smart computing environment. The components and
functionalities of the system 100 are described further in
detail.
[0025] According to an embodiment of the disclosure, a schematic
representation of the placement of a plurality of sensors of system
100 for monitoring fluid pipeline 102 is shown in FIG. 2. FIG. 2
shows a segment of the pipeline 102 containing the plurality of
sensors present at two ends of the segment. It may be appreciated
that the set of sensors are equidistantly along the length of the
pipeline. As shown in the figure, the system 100 comprises four
sensitive vibration sensors for sensing infrasonic range. The four
vibration sensors are referred as a first vibration sensor (A), a
second vibration sensor (B), a third vibration sensor (C) and a
fourth vibration sensor (D). The first vibration sensor (A) is
installed at a first location on the pipeline. The second vibration
sensor (B) is installed at a second location on the pipeline. The
first and the second vibration sensors (A and B) are installed on
the surface of the pipeline. The first location and the second
location are two ends of a segment from amongst a plurality of
segments of the pipeline, wherein the plurality of segments is
distributed along a length of the pipeline at equal distance from
each other. The third vibration sensor (C) is installed at the
first location on ground below the first vibration sensor (A). And
the fourth vibration sensor (D) is installed at the second location
on the ground below the second vibration sensor (A).
[0026] In an example, the sensor C is at a distance of 20 meters
from sensor A and sensor D is at a distance of 20 meters from
sensor B, while, the distance between the sensor A and sensor B are
about 20 kms. Though, it may be appreciated that the distance
between the first location and the second location can be slightly
varied by the user.
[0027] According to an embodiment of the disclosure, the system 100
also comprises a first pressure sensor (P1) and a second pressure
sensor (P2). The first and the second pressure sensors (P1 and P2)
are installed on the pipeline 102 in such a way that their
diaphragm is at direct contact of the fluid inside the pipeline
102. In an example, the first pressure sensor (P1) and the second
pressure sensor (P2) are also installed about 20 kms apart. The
first pressure sensor (P1) is at the first location and the second
pressure sensor (P2) is at the second location. The first location
is referred as the collective location of the first vibration
sensor (A), the third vibration sensor (C) and the first pressure
sensor (P1). The second location is referred as the collective
location of the second vibration sensor (B), the fourth vibration
sensor (D) and the second pressure sensor (P2).
[0028] According to an embodiment of the disclosure, the first
pressure sensor P1 and the second pressure sensor P2 picks up the
negative pressure waves directly, generated due to leakage or theft
in the pipeline 102. The first and the second vibration sensors (A
and B) picks up vibration due to the negative pressure waves at
some degree and also picks up any other disturbances from
surroundings. Any other disturbance from the surrounding may be due
to car or person/animal passing by the pipe, corrosion in the
pipeline or mild seismic vibrations etc. Any other disturbance may
also be captured from any infrasonic noise created on the pipe
surface at large distances. The third and the fourth vibration
sensors (C and D) is configured to pick up the local disturbances,
such as like fluid sloshing due to seismic waves etc.
[0029] The difference between signal captured from the first
vibration sensor (A) and third vibration sensor (C) is A-C, and the
difference between signal captured from the second vibration sensor
(B) and the fourth vibration sensor (D) will be B-D. A-C and B-D
gives signal that are generated on the pipeline surface itself.
These two are configured to capture the negative pressure wave
information (as the fluid carrying the negative pressure wave
vibration will couple to the pipe surface as well) or any
activities on the pipeline at distant locations.
[0030] In the present embodiment, [0031] the difference between the
signals captured from the first vibration sensor (A) and third
vibration sensor (C), i.e., A-C is termed as signal S1, [0032] the
difference between the signals captured from the second vibration
sensor (B) and fourth vibration sensor (D), i.e., B-D is termed as
signal S2. [0033] Similarly, the difference between the signals
captured from the first pressure sensor (P1) and the fourth
vibration sensor (D), i.e., P1-C is termed as signal S3, and [0034]
the difference between the signals captured from the second
pressure sensor (P2) and the third vibration sensor (C), i.e., P2-D
signal is termed as S4.
[0035] Thus, the signal S3 and the signal S4 will be free from any
influence of the local disturbances like fluid sloshing due to
seismic waves etc. Now, these signals are then digitized with GPS
time stamping so that later they can be synchronized while
analyzing by a central server.
[0036] According to an embodiment of the disclosure, a machine
learning classifier model is generated from the signals S1, S2, S3
& S4 using data collected for leakage and no-leakage conditions
(leak can be simulated by opening up some valves) along with slow
oil suctions and human activities as drilling etc. on the pipe
(simulating theft conditions). Once the classifier model is
generated it is applied to detect leak and/or theft in real time.
Since both the negative pressure waves in fluid and infrasound
generated on pipe surface travel at a speed of sound, S1, S2, S3,
S4 signal generated by leakage and theft can be detected in a very
fast manner.
[0037] According to an embodiment of the disclosure, a flowchart
300 illustrating the steps involved in generating the classifier
model is shown in FIG. 3. The model generation comprises four major
steps. In the step 1, leakage condition is simulated in a
controlled environment. The simulation is achieved by opening a
valve in the test segment as sudden leak. Further, differential
input signals S1, S4, S2 & S3 are acquired and digitized for a
predefined time window such as 1 min window. This digitized signal
is then time stamped with GPS data. And finally, the time stamped
data is sent to the central server for storage and labeled as class
1.
[0038] In the step 2, theft condition is simulated in a controlled
environment. The simulation is achieved by slowly opening the valve
and tamper on the pipeline. Further, differential input signals S1,
S4, S2 & S3 are acquired and digitized. This digitized signal
is then time stamped with GPS data. And finally, the time stamped
data is sent to the central server for storage and labeled as class
2.
[0039] In the step 3, normal condition is resumed in the pipeline.
Further, the differential input signals S1, S4, S2 & S3 are
acquired and digitized. This digitized signal is then time stamped
with GPS data. And finally, the time stamped data is sent to the
central server for storage and labeled as class 3.
[0040] In the step 4, a plurality of features is extracted from 1
min time window with 1 second overlaps. The plurality of features
is extracted from one-minute time window of signals S1, S2, S3 and
S4. The plurality of features comprises time-frequency based and
statistical features. Further, features are extracted from all the
windows (joint time-frequency, wavelet, etc.). Finally, a feature
selection algorithm such as principal component analysis (PCA) is
used to generate the classifier model. This classifier model is
then used to classify the input in one of the class 1, class 2 or
class 3.
[0041] According to an embodiment of the disclosure, the system 100
is configured to provide the exact location (X.sub.L) of the
leakage along the segment of the pipeline 102, in case of oil or
gas leakage. On identification of leak event, leak localization
module is triggered. Time delay .DELTA.tl between the signal S3 and
signal S4 is calculated through a signal correlation technique.
With known sound speed in fluid v, leak position X.sub.L can be
calculated by equation 1 (length of the segment L between A and B
is known). Once a leak event is detected, both an alarm is
generated and sent to a server for further action by the monitoring
team
X L = L - v .times. .times. .DELTA. .times. .times. tl 2 ( 1 )
##EQU00001##
[0042] According to an embodiment of the disclosure, the system 100
is also configured to determine the exact location of theft
(X.sub.T) in the segment of pipeline 102 in case of theft. The
equation (1) can be applied on S1 and S2 to localize theft after a
theft event is detected. Here, theft position is X.sub.T, and
.DELTA.tt represents time lag between the signals S3 and S4 and v
is the sound speed in pipe metal.
X T = L - v .times. .times. .DELTA. .times. .times. tt 2 ( 2 )
##EQU00002##
[0043] In operation, referring to FIG. 4A through FIG. 4B, flow
diagram of a method 400 for inspecting and detecting fluid leakage
in a pipeline is described in accordance with an example
embodiment. The method 400 depicted in the flow chart may be
executed by a system, for example, the system, 100 of FIG. 1. In an
example embodiment, the system 100 may be embodied in the computing
device as explained above.
[0044] Operations of the flowchart, and combinations of operation
in the flowchart, may be implemented by various means, such as
hardware, firmware, processor, circuitry and/or other device
associated with execution of software including one or more
computer program instructions. For example, one or more of the
procedures described in various embodiments may be embodied by
computer program instructions. In an example embodiment, the
computer program instructions, which embody the procedures,
described in various embodiments may be stored by at least one
memory device of a system and executed by at least one processor in
the system. Any such computer program instructions may be loaded
onto a computer or other programmable system (for example,
hardware) to produce a machine, such that the resulting computer or
other programmable system embody means for implementing the
operations specified in the flowchart. It will be noted herein that
the operations of the method 400 are described with help of system
100. However, the operations of the method 400 can be described
and/or practiced by using any other system.
[0045] Initially, at step 402 of the method 400, vibration signals
are captured from the first vibration sensor A, the second
vibration sensor B, the third vibration sensor C and the fourth
vibration sensor D. The first vibration sensor A is installed at
the first location on the pipeline 102. The second vibration sensor
B is installed at a second location on the pipeline 102. The first
location and the second location are two ends of a segment from
amongst a plurality of segments of the pipeline 102, wherein the
plurality of segments is distributed along a length of the pipeline
102 at equal distance from each other. The third vibration sensor C
is installed at the first location on ground. And the fourth
vibration sensor D is installed at the second location on the
ground.
[0046] Further, at step 404 of the method 400, the negative
pressure wave signals generated due to leakage in the pipeline 102
are captured using the first pressure sensor P1 and the second
pressure sensor P2. The first pressure sensor P1 is installed at
the first location on the pipeline 102. And the second pressure
sensor P2 is installed at the second location on the pipeline
102.
[0047] Further, at step 406 of the method 400, the first signal
(S1) is calculated as a difference between the signals captured
from the first vibration sensor A and the third vibration sensor C
present at the first location. Similarly, at step 408, the second
signal (S2) is calculated as a difference between the signals
captured from the second vibration sensor B and the fourth
vibration sensor D present at the second location. At step 410, the
third signal (S3) is calculated as a difference between the signals
captured from the first pressure sensor P1 and the third vibration
sensor C. At step 412, the fourth signal (S4) is calculated as a
difference between the signals captured from the second pressure
sensor P2 and the fourth vibration sensor D.
[0048] Further, at step 414 of the method 400, the first signal
(S1), the second signal (S2), the third signal (S3), and the fourth
signal (S4) are digitized along with a global positioning system
(GPS) time stamping. At step 416, the plurality of features is
extracted from a one-minute time window of each of the first signal
(S1), the second signal (S2), the third signal (S3), and the fourth
signal (S4). Further at step 418, a set of features is selected out
of the plurality of features using a feature selection algorithm
such as principle component analysis (PCA), wherein the set of
features are selected based on a user defined condition. The user
defined condition is decided by a user, the user may decide a
certain number to take a top set of features for feature selection
algorithm. While in another example, the complete plurality of
features may also be used for classification.
[0049] At step 420 of the method 400, the selected set of features
is provided to the pre-generated classifier model, wherein the
pre-generated classifier model is generated by simulating a normal
condition, a leakage condition and a theft condition. And finally,
at step 422, at least one of the normal condition, the leakage
condition in the pipeline or the theft condition is detected in the
pipeline 102 using the pre-generated classifier model. The method
400 may also be configured to generate the alarm in case leakage or
theft is detected.
[0050] According to an embodiment of the disclosure, a flowchart
500 is shown in FIG. 5 illustrating the steps involved in
classification using the classifier model. Initially at step 502,
differential inputs S1, S4, S2 & S3 are acquired and digitized
for 1 min window. Further the digitized input is then time stamped
with GPS data and sent to server every after 1 min. At step 504, a
set of predefined features is extracted from the window (joint
time-frequency, wavelet, etc.). At step 506, a feature selection
algorithm is run to select a set of best features based on a
predefined set of criteria used by the feature selection algorithm.
The use of any feature selection algorithm such as principle
component analysis (PCA) is well within the scope of this
disclosure. At step 508, the classifier model is applied to
selected set of features. At step 510, it is checked if it is class
3. If yes then at step 512, window is shifted by 1 second. If no
then at step 514, it is checked if it is class 1. If yes, then at
step 516 leak position is calculated by equation (1) using signal
S3 and signal S4. At step 518, leak position is reported, and an
alarm is generated. Further if the classified class is not class 1,
then at step 520 the theft position is calculated by equation (2)
using signal S1 and S2. And at step 522, theft position is
reported, and the alarm is generated.
[0051] The written description describes the subject matter herein
to enable any person skilled in the art to make and use the
embodiments. The scope of the subject matter embodiments is defined
by the claims and may include other modifications that occur to
those skilled in the art. Such other modifications are intended to
be within the scope of the claims if they have similar elements
that do not differ from the literal language of the claims or if
they include equivalent elements with insubstantial differences
from the literal language of the claims.
[0052] The embodiments of present disclosure herein address
unresolved problem of accurate detection of fluid leakage over a
long distance without detecting ambient interference. The
embodiment thus provides a method and system for detecting and
inspecting fluid leakage in pipelines.
[0053] It is to be understood that the scope of the protection is
extended to such a program and in addition to a computer-readable
means having a message therein; such computer-readable storage
means contain program-code means for implementation of one or more
steps of the method, when the program runs on a server or mobile
device or any suitable programmable device. The hardware device can
be any kind of device which can be programmed including e.g. any
kind of computer like a server or a personal computer, or the like,
or any combination thereof. The device may also include means which
could be e.g. hardware means like e.g. an application-specific
integrated circuit (ASIC), a field-programmable gate array (FPGA),
or a combination of hardware and software means, e.g. an ASIC and
an FPGA, or at least one microprocessor and at least one memory
with software processing components located therein. Thus, the
means can include both hardware means, and software means. The
method embodiments described herein could be implemented in
hardware and software. The device may also include software means.
Alternatively, the embodiments may be implemented on different
hardware devices, e.g. using a plurality of CPUs.
[0054] The embodiments herein can comprise hardware and software
elements. The embodiments that are implemented in software include
but are not limited to, firmware, resident software, microcode,
etc. The functions performed by various components described herein
may be implemented in other components or combinations of other
components. For the purposes of this description, a computer-usable
or computer readable medium can be any apparatus that can comprise,
store, communicate, propagate, or transport the program for use by
or in connection with the instruction execution system, apparatus,
or device.
[0055] The illustrated steps are set out to explain the exemplary
embodiments shown, and it should be anticipated that ongoing
technological development will change the manner in which
particular functions are performed. These examples are presented
herein for purposes of illustration, and not limitation. Further,
the boundaries of the functional building blocks have been
arbitrarily defined herein for the convenience of the description.
Alternative boundaries can be defined so long as the specified
functions and relationships thereof are appropriately performed.
Alternatives (including equivalents, extensions, variations,
deviations, etc., of those described herein) will be apparent to
persons skilled in the relevant art(s) based on the teachings
contained herein. Such alternatives fall within the scope of the
disclosed embodiments. Also, the words "comprising," "having,"
"containing," and "including," and other similar forms are intended
to be equivalent in meaning and be open ended in that an item or
items following any one of these words is not meant to be an
exhaustive listing of such item or items, or meant to be limited to
only the listed item or items. It must also be noted that as used
herein and in the appended claims, the singular forms "a," "an,"
and "the" include plural references unless the context clearly
dictates otherwise.
[0056] Furthermore, one or more computer-readable storage media may
be utilized in implementing embodiments consistent with the present
disclosure. A computer-readable storage medium refers to any type
of physical memory on which information or data readable by a
processor may be stored. Thus, a computer-readable storage medium
may store instructions for execution by one or more processors,
including instructions for causing the processor(s) to perform
steps or stages consistent with the embodiments described herein.
The term "computer-readable medium" should be understood to include
tangible items and exclude carrier waves and transient signals,
i.e., be non-transitory. Examples include random access memory
(RAM), read-only memory (ROM), volatile memory, nonvolatile memory,
hard drives, CD ROMs, DVDs, flash drives, disks, and any other
known physical storage media.
[0057] It is intended that the disclosure and examples be
considered as exemplary only, with a true scope of disclosed
embodiments being indicated by the following claims.
* * * * *